Method and apparatus for identifying cardiac and non-cardiac oversensing using intracardiac electrograms

ABSTRACT

A method and apparatus for automatically identifying various types of cardiac and non-cardiac oversensing and automatically performing a corrective action to reduce the likelihood of oversensing is provided. EGM data, including time intervals between sensed and paced events and signal morphologies, are analyzed for patterns indicative of various types of oversensing, including oversensing of far-field R-waves, R-waves, T-waves, or noise associated with electromagnetic interference, non-cardiac myopotentials, a lead fracture, or a poor lead connection. Identification of oversensing and its suspected cause are reported so that corrective action may be taken. The corrective action may include, for example, adjusting sensing parameters such as blanking periods, decay constants, decay delays, threshold values, sensitivity values, electrode configurations and the like.

This application is a continuation of U.S. patent applications Ser. No.10/418,857, filed Apr. 18, 2003, which is a continuation-in-part (CIP)of U.S. patent application Ser. No. 10/135,080, filed Apr. 29, 2002, theentire content of both of which is incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to a method and apparatus forautomatically identifying cardiac and non-cardiac oversensing by animplantable cardiac device using intracardiac electrogram signals.

BACKGROUND

Implantable medical devices are available to provide therapies forrestoring normal cardiac rhythms by delivering electrical shock therapyfor cardioverting or defibrillating the heart in addition to cardiacpacing. Such a device, commonly known as an implantable cardioverterdefibrillator or “ICD”, senses a patient's heart rhythm and classifiesthe rhythm according to a number of rate zones in order to detectepisodes of tachycardia or fibrillation. Single chamber devices areavailable for treating either atrial arrhythmias or ventriculararrhythmias, and dual chamber devices are available for treating bothatrial and ventricular arrhythmias. Rate zone classifications mayinclude slow tachycardia, fast tachycardia, and fibrillation.

Upon detecting an abnormal rhythm, the ICD delivers an appropriatetherapy. Cardiac pacing is delivered in response to the absence ofsensed intrinsic depolarizations, referred to as P-waves in the atriumand R-waves in the ventricle. In response to tachycardia detection, anumber of tiered therapies may be delivered beginning withanti-tachycardia pacing therapies and escalating to more aggressiveshock therapies until the tachycardia is terminated. Termination of atachycardia is commonly referred to as “cardioversion.” Ventricularfibrillation (VF) is a serious life-threatening condition and isnormally treated by immediately delivering high-energy shock therapy.Termination of VF is normally referred to as “defibrillation.”

In modern implantable cardioverter defibrillators, the physicianprograms the particular anti-arrhythmia therapies into the device aheadof time, and a menu of therapies is typically provided. For example, oninitial detection of an atrial or ventricular tachycardia, ananti-tachycardia pacing therapy may be selected and delivered to thechamber in which the tachycardia is diagnosed or to both chambers. Onredetection of tachycardia, a more aggressive anti-tachycardia pacingtherapy may be scheduled. If repeated attempts at anti-tachycardiapacing therapies fail, a higher energy cardioversion pulse may beselected. For an overview of tachycardia detection and treatmenttherapies reference is made to U.S. Pat. No. 5,545,186 issued to Olsonet al.

Detection of tachycardia or fibrillation may also trigger the storage ofthe sensed intracardiac electrogram (EGM) for a period of severalseconds such that the EGM signals leading up to and during a detectedarrhythmia episode are available for downloading and displaying on anexternal programmer or other device for analysis by a physician. Suchanalysis aids the physician in monitoring the status of the patient andthe patient's response to delivered therapies. Occasionally,cardioversion or defibrillation therapies are delivered when the patientdoes not feel symptomatic. In such cases, the ICD may inappropriatelydetect a tachycardia or fibrillation episode that does not exist anddeliver an anti-arrhythmia therapy when it is not needed. Inappropriatearrhythmia detections may cause a patient to experience painful,repeated shocks within a short period of time. Anti-tachycardia pacingtherapies delivered during normal sinus rhythm can potentially induce anarrhythmia in some patients. For these reasons, the delivery of atherapy in response to inappropriate arrhythmia detection is highlyundesirable.

Inappropriate arrhythmia detection is generally caused by oversensing.Oversensing can be defined as the sensing of events other than the oneP-wave and/or the one R-wave occurring during each normal sinus cardiaccycle. Oversensing of both cardiac and non-cardiac events can result ininappropriate arrhythmia detection by the ICD if the detected rate dueto oversensing falls into an arrhythmia detection zone. Cardiacoversensing refers to oversensing of cardiac events such as far-fieldR-waves, T-waves, or R-waves that are sensed twice and are therefore“double-counted”. Examples of cardiac oversensing are illustrated inFIG. 1. A conventional ECG signal is illustrated showing a normalcardiac cycle indicated by a P-wave, R-wave, and T-wave. Beneath theECG, is a typical ventricular intracardiac electrogram signal (VEGM) inwhich a ventricular signal spike coincides with the R-wave on the ECG.During normal sensing, shown beneath the VEGM, one atrial sensed event(AS) and one ventricular sensed event (VS) occur for each cardiac cycle,corresponding to the atrial P-wave and the ventricular R-wave,respectively.

Far-field R-wave oversensing is illustrated in FIG. 1 in which oneatrial sensed event (AS) per cardiac cycle corresponds to the normalP-wave and a second atrial sensed event (AS) per cardiac cyclecorresponds to the R-wave. Far-field R-waves are sometimes sensed in theatria because the amplitude of an R-wave, as sensed at the atrialsensing electrodes, can reach the atrial sensitivity threshold.Therefore an atrial sensitivity setting required for sensing P-waves mayalso result in sensing of far-field R-waves from the ventricles.

T-wave oversensing is illustrated in FIG. 1 in which two ventricularsensed events (VS) occur during each cardiac cycle, one coinciding withthe R-wave and one coinciding with the T-wave. T-wave oversensing occurswhen the ventricular sensitivity setting is too sensitive, resulting insensing of both R-waves and T-waves. T-wave oversensing also occurs whenthe R-wave amplitude has reduced to a point that causes theauto-adjusting threshold, which is a function of the R-wave, to decreasebelow the T-wave threshold. R-wave oversensing, also referred to as“R-wave double-counting,” is also illustrated in FIG. 1 in which twoventricular sense events (VS) correspond to one R-wave. This“double-counting” of R-waves can occur, for example, when an R-wavecomplex is widened due to conditions such as bundle branch block or widecomplex ventricular tachycardia. For each of these types of cardiacoversensing, generally one extra atrial or ventricular sensed eventoccurs per cardiac cycle, as seen in the illustrations of FIG. 1.

Non-cardiac oversensing refers to undesired sensing of other electricalsignals by an ICD that are not cardiac in origin. Such non-cardiacsignals are generally referred to as “noise.” Noise may occur in theform of myopotentials from surrounding muscle tissue or as the result ofelectromagnetic interference (EMI) external to the patient. Noise mayalso occur when the insulation of a lead fails, a lead conductor becomesfractured, or when a lead is poorly connected to the ICD.

Examples of non-cardiac oversensing are illustrated in FIGS. 2A through2C. In FIG. 2A, a ventricular EGM (VEGM) signal is shown with acorresponding illustration of EMI oversensing. EMI appears as relativelycontinuous high frequency noise on the VEGM and can be repeatedly sensedas a ventricular event (VS) by the ICD. In FIG. 2B, a ventricular EGM(VEGM) is shown with a corresponding illustration of myopotentialoversensing. Myopotentials may appear as lower frequency noise on theVEGM than EMI, resulting in somewhat less frequent but repeatedventricular sensed events (VS). In FIG. 2C, a ventricular EGM (VEGM) isshown corresponding to noise associated with a lead fracture or a poorlead connection. This type of noise can result in saturation of thesense amplifiers and intermittent bursts of noise. Oversensing due to alead fracture or poor lead connection, therefore, produces intermittentclusters of ventricular sensed events (VS), as shown in FIG. 2C. As seenin FIGS. 2A through 2C, non-cardiac oversensing is generally associatedwith multiple oversensed events per cardiac cycle that may beintermittent or continuous, of high or low amplitude, and of relativelylow or high frequency.

Since these problems of oversensing can be rare and are therefore notroutinely encountered in all patients, the task of recognizing andtrouble-shooting oversensing can be a challenging one to the physician.Oversensing may not be recognized until inappropriate arrhythmiadetections are made and unneeded therapies are delivered. While storedEGM data can be useful in identifying and trouble-shooting inappropriatearrhythmia detections due to oversensing, valid arrhythmia detectionsmay occur the majority of the time with only an occasional inappropriatedetection occurring, making the identification of EGM episodesassociated with inappropriate detections a time-consuming task. Once aninappropriate detection is identified, the numerous types of oversensingthat may have caused the detection make diagnosing the problem complex.With a growing number of ICD patients in broad geographicaldistributions, clinicians need to be able to quickly and confidentlydiagnose and correct such problems. What is needed, therefore, is anautomated method for recognizing oversensing and specificallyidentifying the type of oversensing present so that a physician may makeprompt corrective actions with confidence.

SUMMARY

The present invention addresses the problem of oversensing in animplantable cardiac stimulation device and the associated difficultiesin trouble-shooting oversensing problems. Further, the invention isdirected to automatically performing corrective actions upon detectionof oversensing to reduce the likelihood of future oversensing. As willbe described, the corrective actions are dynamically performed to reducethe likelihood of future oversensing. Aspects of the present inventioninclude a method for automatically evaluating EGM data for determiningif oversensing is present and, if so, determining the most likely causeof oversensing. Further aspects of the present invention allowinappropriate arrhythmia detection due to oversensing to be identified.Still further aspects of the present invention include generating areport of an oversensing problem and recommending or automaticallytaking a corrective action to eliminate oversensing. For example, theimplanted device may adjust one or more sensing parameters includingblanking periods, decay constants, decay delays, threshold values,sensitivity values, electrode configurations and the like as correctiveaction to eliminate oversensing. In some embodiments, the implantedmedical device adjusts the sensing parameters iteratively andincrementally a number of times.

Methods included in the present invention may be implemented in anexternal device, such as a programmer or personal computer, for offlineprocessing of EGM data that has been stored in an implanted ICD anduplinked to an external device. The present invention may also beimplemented in an implantable monitor, ICD or pacemaker for eitherpost-processing or real-time processing of EGM data.

In operation, an algorithm is executed for analyzing EGM data, includingtime intervals between sensed and/or paced events and sensed signalmorphologies. This analysis searches for sensed interval patterns thatare indicative of specific types of oversensing, including both cardiacand non-cardiac types of oversensing. Near-field and/or far-field sensedEGM data may be analyzed. The analysis may also include examination ofsignal morphology using template matching to verify specific types ofoversensing. Various types of cardiac oversensing that may be identifiedinclude, but are not limited to, far-field R-wave oversensing, R-waveoversensing, and T-wave oversensing. Non-cardiac causes of oversensingthat may be diagnosed include electromagnetic interference, non-cardiacmyopotentials, a lead fracture, or a poor lead connection.

When methods included in the present invention for recognizingoversensing are implemented in an external device, EGM data that hasbeen stored in an implanted device in response to an arrhythmiadetection or other monitoring algorithm may be uplinked to the externaldevice. The EGM data is analyzed, and, if oversensing is identified, areport is generated to notify a physician of the incidence ofoversensing and its likely cause. The report may optionally recommend acorrective action for eliminating the oversensing based on the type ofoversensing detected.

When methods included in the present invention are implemented in animplantable device, such as an ICD or pacemaker, the EGM analysis may beperformed in response to a triggered storage of an EGM episode or on aperiodic basis to detect oversensing. Recognition of an oversensingproblem may trigger any of a number of responsive actions. A warningflag may be generated to alert a physician of an oversensing problem thenext time a device interrogation is performed. A patient notificationsignal may be generated to notify the patient to seek medical attentionfor correcting the oversensing problem. A corrective action, e.g.,modification of one or more sensing parameters, may be takenautomatically by the implanted device to eliminate oversensing, such asautomatically adjusting an atrial or ventricular sensitivity setting orchanging a sensing electrode configuration. The implanted devicedynamically performs the automatic corrective action, i.e., theimplanted device operates in accordance with originally programmedsensing parameters for a plurality of cardiac cycles, and upon detectingoversensing, the implanted device automatically provides the correctiveaction to avoid future oversensing. Thus, the implanted device performsthe corrective action “on the fly” whenever oversensing is detected. Theimplanted device may further use previously stored cardiac episode datato determine whether the adjusted sensing parameters will properlydetect true cardiac episodes. For example, the implanted device mayapply the adjusted sensing parameters to a previously storedintracardiac electrogram of a previous ventricular fibrillation (VF)episode to determine whether, given the adjusted sensing parameters, theimplanted device is able to correctly identify the VF episode. When theadjusted parameters result in the inability to accurately detect thecardiac episode, the implanted device resets the adjusted parameters totheir original settings.

EGM analysis may also be performed in real-time when methods andapparatus included in the present invention are incorporated in animplantable device. The diagnosis of oversensing in real time maytrigger storage of EGM data as well as generate a warning flag and/or apatient notification signal. A corrective action may also beautomatically taken by the implanted device in order to eliminate theoversensing. For example, the implanted device may modify one or moresensing parameters including blanking periods, decay constants, decaydelays, threshold values, sensitivity values, electrode configurationsand the like. As described, the modifications made to the sensingparameters by implanted medical device can be incremental and iterative.In an ICD, recognition of oversensing allows identification ofinappropriate arrhythmia detections due to oversensing. If arrhythmiadetection is determined to be inappropriate, a scheduled anti-arrhythmiatherapy may optionally be withheld. Alternatively, the arrhythmiatherapy may still be delivered but with a patient notification signal sothat the patient will seek medical attention to correct the oversensingproblem.

Aspects of the present invention, which allow automatic identificationof oversensing, can save a physician considerable time and, moreover,prevent inappropriate arrhythmia detections from going unnoticed. Onceoversensing is identified and its probable cause diagnosed, promptcorrective action may be taken so that accurate sensing of heart rhythmsmay be achieved and appropriate stimulation therapies delivered only asneeded. Repeated delivery of unnecessary cardioversion or defibrillationtherapies in response to inappropriate arrhythmia detections due tooversensing may be avoided. The methods included in the presentinvention may advantageously be implemented in a central computersystem, a network or web-based system, allowing a physician to remotelydiagnose an oversensing problem. Alternatively, the methods andapparatus included in the present invention may be implemented in animplanted device so that corrective action may be performedautomatically to eliminate oversensing.

In one embodiment, the invention provides a method comprising operatingan implanted medical device in accordance with sensing parameters for aplurality of cardiac cycles, identifying oversensing by the implantedmedical device, and automatically adjusting at least one of the sensingparameters of the implanted medical device in response to identifyingthe oversensing.

In another embodiment, the invention provides a computer-readable mediumcomprising instructions to cause a processor to operate an implantedmedical device in accordance with sensing parameters for a plurality ofcardiac cycles, identify oversensing by the implanted medical device,and automatically adjust at least one sensing parameter of the implantedmedical device in response to identifying the oversensing.

In a further embodiment, the invention provides an implantable medicaldevice comprising at least one sensing electrode to sense cardiac datafrom a heart of a patient in accordance with programmed sensingparameters for a plurality of cardiac cycles and a processor to identifyoversensing by the implantable medical device based on the sensedcardiac data and automatically adjust at least one of the sensingparameter of the implantable medical device in response to identifyingthe oversensing.

In another embodiment, the invention provides an implantable medicaldevice comprising means for operating an implantable medical device inaccordance with sensing parameters for a plurality of cardiac cycles,means for identifying oversensing by the implantable medical device, andmeans for automatically performing a corrective action to reduce thelikelihood of oversensing.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features andinventive aspects of the invention will be apparent from the descriptionand drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is an illustration of a normal ECG signal, a correspondingventricular EGM signal, and corresponding illustrations of sensed eventsoccurring during normal sensing, far-field R-wave oversensing, T-waveoversensing, and R-wave oversensing.

FIG. 2A is an illustration of a ventricular EGM signal with noise due toelectromagnetic interference (EMI) and a corresponding example of EMIoversensing.

FIG. 2B is an illustration of a ventricular EGM signal with myopotentialnoise and a corresponding example of myopotential oversensing.

FIG. 2C is an illustration of a ventricular EGM signal with noise due toa lead fracture or poor lead connection and a corresponding example ofoversensing.

FIG. 3 is an illustration of an implantable cardiac stimulation devicecapable of pacemaking, cardioversion, and defibrillation incommunication with a patient's heart via three stimulation and sensingleads.

FIG. 4 is a functional, block diagram of the implantable pacemakercardioverter defibrillator shown in FIG. 3.

FIG. 5 is a flow chart providing an overview of one embodiment of thepresent invention for automatically identifying oversensing from EGMdata stored in the ICD shown in FIG. 4 and uplinked to an externaldevice.

FIG. 6 is a flow chart providing an overview of another embodiment ofthe present invention implemented in the ICD shown in FIG. 4 forautomatically identifying oversensing in real time.

FIGS. 7 and 8 depict a flow chart summarizing a method that may be usedin the embodiments of FIG. 5 or 6 for automatically identifyinginappropriate arrhythmia detection due to oversensing.

FIG. 9 is a flow chart illustrating a method for detecting a cardiacoversensing interval pattern that may be used in one embodiment of themethod shown in FIGS. 7 and 8;

FIG. 10 is a flow chart illustrating a method for identifyingalternating signal morphologies that may be used in one embodiment ofthe method shown in FIGS. 7 and 8 for identifying the occurrence ofT-wave oversensing.

FIG. 11 is a flow chart illustrating a method for detecting noise burststhat may be used in one embodiment of the method shown in FIGS. 7 and 8for diagnosing a lead fracture or poor lead connection.

FIG. 12 is an exemplary cardiac electrogram illustrating T-waveoversensing as well as exemplary automatic corrective actions to reducethe likelihood of T-wave oversensing.

FIG. 13 is an exemplary cardiac electrogram illustrating R-waveoversensing as well as exemplary automatic corrective actions to reducethe likelihood of R-wave oversensing.

DETAILED DESCRIPTION

The present invention is aimed at providing a system and method forautomatically identifying and trouble-shooting cardiac and/ornon-cardiac oversensing by an implantable cardiac stimulation device.The methods included in the present invention may be used in conjunctionwith, or incorporated in, an implantable cardiac stimulation device suchas a pacemaker or an implantable cardioverter defibrillator (ICD), orother monitoring devices, capable of storing sensed intracardiacelectrogram (EGM) data.

An exemplary ICD 10 is shown in FIG. 3, with which methods included inthe present invention may be used. In accordance with the invention, ICD10 identifies oversensing and automatically provides a correctiveaction, e.g., adjusts one or more sensing parameters or electrodeconfigurations to avoid future oversensing. Particularly, ICD 10operates in accordance with originally programmed sensing parameters fora plurality of cardiac cycles, and upon detecting oversensing,automatically provides the corrective action to avoid futureoversensing. In this manner, the corrective actions provided by ICD 10to avoid future oversensing are dynamically performed.

The ICD 10 is shown coupled to a heart of a patient by way of threeleads 6, 15, and 16. A connector block 12 receives the proximal end of aright ventricular lead 16, a right atrial lead 15 and a coronary sinuslead 6, used for positioning electrodes for sensing and stimulation inthree or four heart chambers. In FIG. 3, right ventricular lead 16 ispositioned such that its distal end is in the right ventricle forsensing right ventricular cardiac signals and delivering pacing orshocking pulses in the right ventricle. For these purposes, rightventricular lead 16 is equipped with a ring electrode 24, an extendablehelix electrode 26 mounted retractably within an electrode head 28, anda coil electrode 20, each of which are connected to an insulatedconductor within the body of lead 16. The proximal end of the insulatedconductors are coupled to corresponding connectors carried by bifurcatedconnector 14 at the proximal end of lead 16 for providing electricalconnection to the ICD 10.

The right atrial lead 15 is positioned such that its distal end is inthe vicinity of the right atrium and the superior vena cava. Lead 15 isequipped with a ring electrode 21 and an extendable helix electrode 17,mounted retractably within electrode head 19, for sensing and pacing inthe right atrium. Lead 15 is further equipped with a coil electrode 23for delivering high-energy shock therapy. The ring electrode 21, thehelix electrode 17 and the coil electrode 23 are each connected to aninsulated conductor with the body of the right atrial lead 15. Eachinsulated conductor is coupled at its proximal end to a connectorcarried by bifurcated connector 13.

The coronary sinus lead 6 is advanced within the vasculature of the leftside of the heart via the coronary sinus and great cardiac vein. Thecoronary sinus lead 6 is shown in the embodiment of FIG. 3 as having adefibrillation coil electrode 8 that may be used in combination witheither the coil electrode 20 or the coil electrode 23 for deliveringelectrical shocks for cardioversion and defibrillation therapies. Inother embodiments, coronary sinus lead 6 may also be equipped with adistal tip electrode and ring electrode for pacing and sensing functionsin the left chambers of the heart. The coil electrode 8 is coupled to aninsulated conductor within the body of lead 6, which provides connectionto the proximal connector 4.

The electrodes 17 and 21 or 24 and 26 may be used as true bipolar pairs,commonly referred to as a “tip-to-ring” configuration. Further,electrode 17 and coil electrode 20 or electrode 24 and coil electrode 23may be used as integrated bipolar pairs, commonly referred to as a“tip-to-coil” configuration. In accordance with the invention, ICD 10may, for example, adjust the electrode configuration from a tip-to-ringconfiguration, e.g., true bipolar sensing, to a tip-to-coilconfiguration, e.g., integrated bipolar sensing, upon detection ofoversensing in order to reduce the likelihood of future oversensing. Inother words, the electrode polarities can be reselected in response todetection of oversensing in an effort to reduce susceptibility ofoversensing. In some cases, electrodes 17, 21, 24, and 26 may be usedindividually in a unipolar configuration with the device housing 11serving as the indifferent electrode, commonly referred to as the “can”or “case” electrode.

The device housing 11 may also serve as a subcutaneous defibrillationelectrode in combination with one or more of the defibrillation coilelectrodes 8, 20 or 23 for defibrillation of the atria or ventricles. Itis recognized that alternate lead systems may be substituted for thethree lead system illustrated in FIG. 3. While a particularmulti-chamber ICD and lead system is illustrated in FIG. 3,methodologies included in the present invention may adapted for use withany single chamber, dual chamber, or multi-chamber ICD or pacemakersystem, or other cardiac monitoring device.

A functional schematic diagram of the ICD 10 is shown in FIG. 4. Thisdiagram should be taken as exemplary of the type of device with whichthe invention may be embodied and not as limiting. The disclosedembodiment shown in FIG. 4 is a microprocessor-controlled device, butthe methods of the present invention may also be practiced with othertypes of devices such as those employing dedicated digital circuitry.

With regard to the electrode system illustrated in FIG. 3, ICD 10 isprovided with a number of connection terminals for achieving electricalconnection to the leads 6, 15, and 16 and their respective electrodes. Aconnection terminal 311 provides electrical connection to the housing 11for use as the indifferent electrode during unipolar stimulation orsensing. The connection terminals 320, 310, and 318 provide electricalconnection to coil electrodes 20, 8 and 23 respectively. Each of theseconnection terminals 311, 320, 310, and 318 are coupled to the highvoltage output circuit 234 to facilitate the delivery of high energyshocking pulses to the heart using one or more of the coil electrodes 8,20, and 23 and optionally the housing 11.

The connection terminals 317 and 321 provide electrical connection tothe helix electrode 17 and the ring electrode 21 positioned in the rightatrium. The connection terminals 317 and 321 are further coupled to anatrial sense amplifier 204 for sensing atrial signals such as P-waves.The connection terminals 326 and 324 provide electrical connection tothe helix electrode 26 and the ring electrode 24 positioned in the rightventricle. The connection terminals 326 and 324 are further coupled to aventricular sense amplifier 200 for sensing ventricular signals.

The atrial sense amplifier 204 and the ventricular sense amplifier 200preferably take the form of automatic gain controlled amplifiers withadjustable sensitivity. In accordance with the invention, ICD 10 and,more specifically, microprocessor 224 automatically adjusts thesensitivity of atrial sense amplifier 204, ventricular sense amplifier200 or both in response to detection of oversensing in order to reducethe likelihood of oversensing. Ventricular sense amplifier 200 andatrial sense amplifier 204 operate in accordance with originallyprogrammed sensing parameters for a plurality of cardiac cycles, andupon detecting oversensing, automatically provides the corrective actionto avoid future oversensing. In this manner, the adjustments provided byICD 10 to amplifiers 200 and 204 to avoid future oversensing are dynamicin nature. Particularly, microprocessor 224 increases a sensitivityvalue of the amplifiers, thus reducing the sensitivity, when oversensingis detected. Atrial sense amplifier 204 and ventricular sense amplifier200 receive timing information from pacer timing and control circuitry212. Specifically, atrial sense amplifier 204 and ventricular senseamplifier 200 receive blanking period input, e.g., ABLANK and VBLANK,respectively, which indicates the amount of time the electrodes are“turned off” in order to prevent saturation due to an applied pacingpulse or defibrillation shock. As will be described, the blankingperiods of atrial sense amplifier 204 and ventricular sense amplifier200 and, in turn, the blanking periods of sensing electrodes associatedwith the respective amplifiers may be automatically adjusted by ICD 10to reduce the likelihood of oversensing. The general operation of theventricular sense amplifier 200 and the atrial sense amplifier 204 maycorrespond to that disclosed in U.S. Pat. No. 5,117,824, by Keimel, etal., incorporated herein by reference in its entirety. Whenever a signalreceived by atrial sense amplifier 204 exceeds an atrial sensitivity, asignal is generated on the P-out signal line 206. Whenever a signalreceived by the ventricular sense amplifier 200 exceeds a ventricularsensitivity, a signal is generated on the R-out signal line 202.

Switch matrix 208 is used to select which of the available electrodesare coupled to a wide band amplifier 210 for use in digital signalanalysis. Selection of the electrodes is controlled by themicroprocessor 224 via data/address bus 218. The selected electrodeconfiguration may be varied as desired for the various sensing, pacing,cardioversion and defibrillation functions of the ICD 10. Specifically,microprocessor 224 may modify the electrode configurations based ondetection of oversensing due to cardiac or non-cardiac origins. Upondetection of R-wave oversensing, for example, microprocessor 224 maymodify the electrode configuration of the right ventricle from truebipolar sensing, e.g., tip-to-ring, to integrated bipolar sensing, e.g.,tip-to-coil.

Signals from the electrodes selected for coupling to bandpass amplifier210 are provided to multiplexer 220, and thereafter converted tomulti-bit digital signals by A/D converter 222, for storage in randomaccess memory 226 under control of direct memory access circuit 228.Microprocessor 224 may employ digital signal analysis techniques tocharacterize the digitized signals stored in random access memory 226 torecognize and classify the patient's heart rhythm employing any of thenumerous signal processing methodologies known in the art. An exemplarytachyarrhythmia recognition system is described in U.S. Pat. No.5,545,186 issued to Olson et al, incorporated herein by reference in itsentirety.

Upon detection of an arrhythmia, an episode of EGM data, along withsensed intervals and corresponding annotations of sensed events, arepreferably stored in random access memory 226. The EGM signals storedmay be sensed from programmed near-field and/or far-field sensingelectrode pairs. Typically, a near-field sensing electrode pair includesa tip electrode and a ring electrode located in the atrium or theventricle, such as electrodes 17 and 21 or electrodes 26 and 24. Afar-field sensing electrode pair includes electrodes spaced furtherapart such as any of: the defibrillation coil electrodes 8, 20 or 23with housing 11; a tip electrode 17 or 26 with housing 11; a tipelectrode 17 or 26 with a defibrillation coil electrode 20 or 23; oratrial tip electrode 17 with ventricular ring electrode 24. The use ofnear-field and far-field EGM sensing of arrhythmia episodes is describedin U.S. Pat. No. 5,193,535, issued to Bardy, incorporated herein byreference in its entirety. Annotation of sensed events, which may bedisplayed and stored with EGM data, is described in U.S. Pat. 4,374,382issued to Markowitz, incorporated herein by reference in its entirety.

The telemetry circuit 330 receives downlink telemetry from and sendsuplink telemetry to an external programmer, as is conventional inimplantable anti-arrhythmia devices, by means of an antenna 332. Data tobe uplinked to the programmer and control signals for the telemetrycircuit are provided by microprocessor 224 via address/data bus 218. EGMdata that has been stored upon arrhythmia detection or as triggered byother monitoring algorithms may be uplinked to an external programmerusing telemetry circuit 330. Received telemetry is provided tomicroprocessor 224 via multiplexer 220. Numerous types of telemetrysystems known in the art for use in implantable devices may be used.

The remainder of the circuitry illustrated in FIG. 4 is an exemplaryembodiment of circuitry dedicated to providing cardiac pacing,cardioversion and defibrillation therapies. The pacer timing and controlcircuitry 212 includes programmable digital counters which control thebasic time intervals associated with various single, dual ormulti-chamber pacing modes or anti-tachycardia pacing therapiesdelivered in the atria or ventricles. Pacer circuitry 212 alsodetermines the amplitude of the cardiac pacing pulses under the controlof microprocessor 224.

During pacing, escape interval counters within pacer timing and controlcircuitry 212 are reset upon sensing of R-waves or P-waves as indicatedby signals on lines 202 and 206, respectively. In accordance with theselected mode of pacing, pacing pulses are generated by atrial paceroutput circuit 214 and ventricular pacer output circuit 216. The paceroutput circuits 214 and 216 are coupled to the desired electrodes forpacing via switch matrix 208. The escape interval counters are resetupon generation of pacing pulses, and thereby control the basic timingof cardiac pacing functions, including anti-tachycardia pacing.

The durations of the escape intervals are determined by microprocessor224 via data/address bus 218. The value of the count present in theescape interval counters when reset by sensed R-waves or P-waves can beused to measure R-R intervals and P-P intervals for detecting theoccurrence of a variety of arrhythmias.

The microprocessor 224 includes associated read-only memory (ROM) inwhich stored programs controlling the operation of the microprocessor224 reside. A portion of the random access memory (RAM) 226 may beconfigured as a number of recirculating buffers capable of holding aseries of measured intervals for analysis by the microprocessor 224 forpredicting or diagnosing an arrhythmia.

In response to the detection of tachycardia, anti-tachycardia pacingtherapy can be delivered by loading a regimen from microprocessor 224into the pacer timing and control circuitry 212 according to the type oftachycardia detected. In the event that higher voltage cardioversion ordefibrillation pulses are required, microprocessor 224 activates thecardioversion and defibrillation control circuitry 230 to initiatecharging of the high voltage capacitors 246 and 248 via charging circuit236 under the control of high voltage charging control line 240. Thevoltage on the high voltage capacitors is monitored via a voltagecapacitor (VCAP) line 244, which is passed through the multiplexer 220.When the voltage reaches a predetermined value set by microprocessor224, a logic signal is generated on the capacitor full (CF) line 254,terminating charging. The defibrillation or cardioversion pulse isdelivered to the heart under the control of the pacer timing and controlcircuitry 212 by an output circuit 234 via a control bus 238. The outputcircuit 234 determines the electrodes used for delivering thecardioversion or defibrillation pulse and the pulse wave shape.

In one embodiment, the ICD 10 may be equipped with a patientnotification system 150. Any patient notification method known in theart may be used such as generating perceivable twitch stimulation or anaudible sound. A patient notification system may include an audiotransducer that emits audible sounds including voiced statements ormusical tones stored in analog memory and correlated to a programming orinterrogation operating algorithm or to a warning trigger event asgenerally described in U.S. Pat. No. 6,067,473 issued to Greeninger etal., incorporated herein by reference in its entirety.

In FIG. 5 a flow diagram is shown providing an overview of theoperations included in a preferred embodiment of the present inventionfor identifying oversensing and diagnosing the type of oversensing thatis occurring. Stored EGM data in response to arrhythmia detection may beanalyzed according to the methods shown in FIG. 5 in order to identifyif an arrhythmia detection is inappropriate due to oversensing. StoredEGM data triggered by other monitoring algorithms besides arrhythmiadetection, such as the monitoring algorithm described in U.S. Pat. No.5,776,168 issued to Gunderson, incorporated herein by reference in itsentirety, may also be analyzed for the presence of oversensing using themethods of FIG. 5.

The operations shown in FIG. 5 are preferably implemented in an externalprogrammer, personal computer or other external device for off-lineprocessing of EGM data stored in an implanted device, such as the ICD 10shown in FIG. 4. At step 395, stored EGM episodes are uplinked viatelemetry circuit 330 to the external device. Stored episode datapreferably includes an EGM signal, sensed and/or paced interval data andcorresponding annotations of sensed and/or paced events. If the episodedata is stored in response to an arrhythmia detection, EGM data leadingup to and including the arrhythmia episode is stored and uplinked to theexternal device for analysis. Such data storage is provided incommercially available devices, for example in the Model 7275 GEM® IIIDual Chamber Implantable Cardioverter Defibrillator available fromMedtronic, Inc., Minneapolis, Minn.

Program code stored in memory of the external programmer or anothermicroprocessor-controlled device is executed at step 400 to analyze theEGM episode data offline. For example, uplinked EGM data may be saved toa diskette for offline processing at a later time or may be transferredvia Internet to a central computer for analysis at a remote location.Reference is made to U.S. Patent Application Serial No. 20010031997entitled “Instrumentation and software for remote monitoring andprogramming of implantable medical devices (IMDs)” to Lee, and U.S.Patent Application Serial No. 20010037366 entitled “System and methodfor providing remote expert communications and video capabilities foruse during a medical procedure” to Webb et al., both patentsincorporated herein by reference in their entirety.

As will be described in detail with reference to FIGS. 7 and 8, analysisof the EGM data includes evaluation of sensed and/or paced intervalpatterns and signal morphology to allow incidents of cardiac ornon-cardiac oversensing to be recognized. If oversensing is identified,as determined at decision step 550, a report is generated at step 555indicating the suspected type of oversensing detected. In oneembodiment, a corrective action may be recommended at step 555 based onthe type of oversensing identified. A recommended corrective action maybe any of: reprogramming a sensing parameter, e.g., sensitivity value,blanking period, sensing decay constant, sensing decay delay,auto-adjusting sensitivity threshold, reprogramming a sensing electrodeconfiguration, tightening set screws in the connector block 12 of theICD 10, investigating for a likely lead fracture that requires repair orlead replacement, or other actions aimed at eliminating oversensing. Ifno oversensing is identified at decision step 550, the operations shownin FIG. 5 are terminated at step 560.

The operations shown in FIG. 5 could alternatively be performed by theimplanted ICD 10 as post-processing of stored EGM episode data. Programcode may be stored in microprocessor 224 for analyzing stored EGMepisode data, for example subsequent to an arrhythmia detection, or on aperiodic basis. If oversensing is identified at decision step 550, areport may be generated at step 555 that will be uplinked to an externalprogrammer the next time the ICD 10 is interrogated. The report maynotify a physician of the date and time that an episode of oversensingwas identified along with the suspected cause, such as R-waveoversensing, T-wave oversensing, P-wave oversensing, lead fracture, orotherwise. The report may further recommend a corrective action, such asreprogramming ventricular sensitivity, repair or replace a lead, orotherwise. Alternatively or additionally, a patient warning signal maybe generated by patient notification circuitry 150 at the time that anoversensing episode is identified, advising the patient to seek medicalattention.

In FIG. 6, a flow chart is shown providing an overview of the operationsincluded in the present invention when it is embodied in an implantableICD, such as ICD 10, to allow real-time EGM analysis to be performed.Real-time EGM analysis allows oversensing to be identified as it occurs,for example before a cardioversion or defibrillation therapy isdelivered in response to inappropriate arrhythmia detection due tooversensing. In the embodiment shown in FIG. 6, the EGM analysisperformed at step 400 is triggered by arrhythmia detection at step 395.The EGM analysis may, for example, include comparing characteristics ofcardiac electrograms to determine whether the detected cardiac event isa false detection due to oversensing. Specifically, EGM analysisperformed at step 400 determines the origin of oversensing, ifoversensing occurred, as well as corrective actions that may be taken toprevent the likelihood of future oversensing. If the EGM analysisresults in oversensing being identified at decision step 550, storage ofthe EGM episode including the oversensing may be triggered at step 565.The stored EGM may then be uplinked to an external device at a latertime for analysis by a physician to allow verification of the detectedoversensing and for determining a corrective action.

Since the detected arrhythmia is an inappropriate detection due tooversensing, any scheduled anti-arrhythmia therapy may optionally becancelled by the ICD 10 at step 570. If a therapy is cancelled, apatient notification signal may be generated at step 570 advising thepatient to seek medical attention.

Even if oversensing is identified at step 550 and a detected arrhythmiais therefore suspected to be an inappropriate detection, a scheduledarrhythmia therapy may still be delivered to ensure that a therapy isnot withheld when it is actually needed. A report of the oversensing andthe suspected cause, however, are generated at step 575 in the mannerdescribed previously, so that corrective action taken by a physician, orautomatically by the ICD 10, may be performed to prevent futureinappropriate arrhythmia detections and unneeded delivery ofcardioversion or defibrillation therapies. In accordance with theinvention, ICD 10 automatically performs a corrective action based onthe suspected cause of oversensing at step 575 to prevent futureinappropriate arrhythmia detections and unneeded delivery ofcardioversion or defibrillation therapies. The automatic correctiveaction is dynamic, in that ICD 10 operates in accordance with originallyprogrammed sensing parameters for a plurality of cardiac cycles, andupon detecting oversensing, ICD 10 automatically provides the correctiveaction to avoid future oversensing. Thus, ICD 10 performs the correctiveaction “on the fly” whenever oversensing is detected. The correctiveaction may include, for example, automatically adjusting sensingparameters, such as automatically resetting a programmed sensitivity,automatically adjusting a blanking period following delivery of a pace,automatically adjusting a programmed decay constant of a sensingelectrode, or automatically resetting a programmed sensing electrodeconfiguration, e.g., from Vtip-Vring to Vtip-Vcoil. In some embodiments,the automatic corrective action is performed iteratively andincrementally, and after each adjustment ICD 10 determines whetheroversensing persists. The automatic corrective action taken by ICD 10may be dependent on the type of oversensing detected. For instance, ICD10 may take different corrective actions for oversensing caused byR-wave double counting as opposed to oversensing caused by T-waveoversensing or myopotential oversensing.

Upon adjusting one or more sensing parameters of ICD 10, microprocessor224 determines whether ICD 10 will appropriately detect a true cardiacepisode with the adjusted sensing parameters at step 576. In someembodiments, microprocessor 224 applies the adjusted sensing parametersto sense previously recorded cardiac episode data stored in memorywithin the ICD. The episode data is a previously recorded intracardialelectrogram of a cardiac episode. Microprocessor 224 can, for example,deliver a waveform of the previously recorded intracardial electrogramto the inputs of sense amplifiers 200 and 204 via switch matrix 208.Microprocessor 224 applies the adjusted sensing parameters in order todetermine whether, given the adjusted sensing parameters, ICD 10 is ableto correctly detect true cardiac episodes. In this manner, the waveformsof the previously recorded intracardial electrogram are delivered withinICD 10, eliminating the need to induce a cardiac episode, such as VF, ofthe heart of the patient, which may be very painful for the patient.

When microprocessor 224 determines that the adjusted sensing parametersresult in the inability of ICD 10 to detect true cardiac episodes,microprocessor 224 resets the sensing parameters to the originalsettings at step 577. For example, if the sensitivity of the sensingelectrode was decreased such that ICD 10 no longer accurately detectstrue capture of the heart, microprocessor 224 may reset the sensitivityto the original value that caused oversensing. In this manner, IMD 10errs on the side of delivering an unnecessary therapy as opposed to notdelivering a necessary therapy.

A report of the oversensing and the suspected cause is generated at step578 in the manner described previously, for a physician. In the casethat the automatic corrective action sufficiently detects true cardiacepisodes, the report may include the automatic corrective actions takenso that the physician is notified of the changes. Further, in the casethat the adjusted parameters were reset to their original values, acorrective action may be recommended by ICD 10 that the physicianperforms to prevent future inappropriate arrhythmia detections andunneeded delivery of cardioversion or defibrillation therapies. In thismanner, upon device interrogation, the physician will be made aware ofthe identified oversensing, its likely cause and any automatedcorrective actions taken and thus be able to make therapeutic decisionsbased on this information. Additionally or alternatively, a patientnotification signal may be issued, advising the patient to seek medicalattention. The report generated at step 575 may include any automaticcorrective actions taken by the ICD 10 such that the physician isnotified of such changes.

If oversensing is not identified at decision step 550 and an arrhythmiahas been detected, programmed anti-arrhythmia therapies are delivered bythe ICD 10 at step 580. EGM episode data may be stored as normallyperformed during ICD 10 operation upon an arrhythmia detection.

A preferred embodiment of a method for analyzing EGM data performed atstep 400 in FIGS. 5 and 6 is summarized in the flow chart shown in FIGS.7 and 8. The method 400 shown in FIGS. 7 and 8 is aimed at identifyinginappropriate arrhythmia detections due to oversensing and determiningthe cause of the oversensing. Therefore, the method 400 is performed toanalyze EGM episode data, associated with arrhythmia detection. However,it is recognized that the methods of FIGS. 7 and 8 can be adapted toanalyze EGM data associated with triggering events of other monitoringalgorithms. If the method 400 is performed offline, a stored EGMassociated with an arrhythmia detection is loaded at step 405. Duringonline analysis, an arrhythmia detection is recognized at step 405 andtriggers the subsequent analysis.

The EGM episode data, including signal morphology, sensed and/or pacedintervals, and sensed and/or paced event annotations, immediately priorto arrhythmia detection will be analyzed by the method 400. The datasegment to be analyzed preferably includes on the order of 10 to 25sensed intervals leading up to arrhythmia detection. The analysispreferably excludes EGM data immediately following a pacing pulse, forexample 120 milliseconds of data following a pacing pulse, in order toeliminate pacing polarization artifacts from the data analysis. Theanalysis also preferably excludes the first 200 milliseconds of a storedEGM episode in order to exclude saturation of the EGM amplifier 210,which typically occurs when the EGM amplifier is first enabled.

At decision step 410, the analysis 400 determines if the arrhythmia hasbeen intentionally induced during electrophysiological testing.Electrophysiological testing is generally performed to determine thesusceptibility of a patient to arrhythmias and to aid in selectingprogrammable therapy options. An arrhythmia may be induced by methodsknown in the art, such as delivering a shock or pacing pulsescoincidentally with the T-wave or delivering a 50-Hz burst. Any of theseinduction methods will be associated with annotated induction eventsstored with the EGM data. The annotated events may be used toautomatically discriminate between induced arrhythmia episodes andspontaneous arrhythmia episodes. If an arrhythmia is detected at or nearthe time of an arrhythmia induction, the detection is classified as anappropriate detection at step 415, and the method 400 is terminated.When the method 400 is embodied in the ICD 10 for real-time episodeanalysis, the analysis can preferably be enabled or disabled by aprogramming command, allowing a physician to disable the method 400during electrophysiological testing.

If a detected arrhythmia is not related to an induction, the method 400determines if the detected arrhythmia is ventricular fibrillation (VF)as detected by the device in order to exclude ventricular tachycardia(VT) episodes at decision step 420. If VF is not detected, meaning theepisode was detected as ventricular tachycardia (VT), the method 400determines at decision step 425 if the interval pattern isrepresentative of far-field R-wave sensing. Far-field R-wave sensingoccurs when the ventricular R-wave is sensed by the atrial senseamplifier 204 resulting in a signal on P-out signal line 206.Intermittent oversensing of the far-field R-wave leads to inappropriateVT detection because the interval patterns are not representative ofatrial fibrillation, atrial flutter or consistent far-field R-waveoversensing. A method for identifying the likelihood that events sensedin the atrium are in fact far-field R waves, rather than P waves, isdescribed in the previously incorporated U.S. Pat. No. 5,545,186 issuedto Olson et al. If an intermittent far-field R-wave pattern is present,the method 400 identifies the episode as an inappropriate arrhythmiadetection due to far-field R-wave oversensing at step 430. As describedabove, ICD 10 may determine a recommended corrective action to reducethe likelihood of oversensing at step 521 (FIG. 8). Possible correctiveactions for far-field R-wave oversensing include, for example,reprogramming an atrial sensitivity value to decrease the sensitivity ofthe atrial electrode, reconfiguring the electrode configuration orpolarity of an atrial lead, or the like. In addition, in someembodiments, ICD 10 automatically performs the recommended correctiveactions in accordance with the invention. If a far-field R-wave patternis not present, oversensing is not identified. The EGM episode isidentified as an appropriate arrhythmia detection at step 415, and themethod 400 is complete.

If the arrhythmia is detected as VF at decision step 420, the method 400evaluates the detected interval regularity at step 435. A VF detectionmay be a true VF episode, but it may also be ventricular tachycardia(VT) or supraventricular tachycardia detected as VF if the rate is highenough to fall into the VF detection zone. High rate VT is the mostcommon arrhythmia that can be detected as VF. During a VT episode, thesensed intervals will be relatively regular compared to intervalsassociated with oversensing of cardiac events or noise. One method forevaluating the interval regularity in order to differentiate a VFdetection due to a high rate VT from a VF detection due to oversensingis to calculate a sum of successive interval differences. For example,the difference between each consecutive pair of intervals for a givennumber of the most recent intervals leading up to VF detection may besummed. If the sum of these consecutive interval differences is lessthan a predetermined maximum, the intervals are considered regular. Forexample, a criterion for detecting interval regularity may require thatthe sum of 12 consecutive interval differences be less than 150milliseconds. If interval regularity is detected, the method 400identifies the episode as an appropriate arrhythmia detection at step437, and the EGM analysis is complete.

If the intervals are determined to be irregular at decision step 435,the method 400 continues to decision step 440 to determine if aninterval pattern indicative of cardiac oversensing is present. As shownpreviously in FIG. 1, cardiac oversensing in the ventricle can includeoversensing of T-waves or R-waves. In these cases of cardiacoversensing, one extra ventricular sensed event occurs during eachcardiac cycle.

One method for recognizing a pattern indicative of cardiac oversensingis summarized by the flow chart shown in FIG. 9. The method 700 comparesa sensed R-R interval to previous R-R intervals to determine if the R-Rinterval is a true R-R interval or, together with a previous interval,forms a true R-R interval. The term “R-R interval” herein refers to theinterval between two events sensed in the ventricle. These events may ormay not be real R-waves, therefore a sensed R-R interval may be aninterval between various oversensed events and R-waves. If oneintervening oversensed event has caused the true R-R interval to bedivided into two intervals then the sum of two intervals will equal thetrue R-R interval. By examining for interval patterns that arerepresentative of one oversensed event occurring per cardiac cycle,cardiac oversensing can be discriminated from oversensing due to other,non-cardiac sources, such as EMI or a lead fracture, which wouldtypically occur more frequently during a cardiac cycle.

The method 700 for recognizing a cardiac oversensing pattern begins atstep 702 by initializing an interval counter (I) to a value of 0. Thisinterval counter will count the number of intervals included in theanalysis performed by method 700 beginning with the interval upon whichthe VF detection was made, referred to as RR(0), and including a givennumber of intervals prior to the VF detection, preferably on the orderof 12 intervals. At step 702, a second counter used for counting thenumber of intervals identified as being associated with a cardiacoversensed event is also initialized to a value of zero. In a preferredembodiment, patterns of cardiac oversensing are recognized by comparinga sensed R-R interval to each of: 1) the previous R-R interval, 2) theR-R interval prior to the previous interval, 3) the sum of the twoprevious intervals, and 4) the absolute value of the difference of thetwo previous intervals. If cardiac oversensing is occurring, at leastone of these four comparisons will match.

These comparisons are made at decision steps 704, 706, 708 and 710. Atstep 704, the interval occurring at VF detection, RR(0), is compared tothe next previous interval RR(−1). If RR(−1) is within 10% of RR(0),these intervals are approximately equal, and an oversensing intervalcounter is increased to one at step 712. To allow for small fluctuationsthat can normally occur in cardiac sensed intervals, the comparisonsmade at steps 704, 706, 708, and 710 are calculated as a ratio of theinterval difference to the interval being analyzed, RR(I), and thatratio is compared to a value close to zero, such as 0.1, which isselected by a the physician, in order to allow for a normal 10%variation in detected cardiac intervals.

At step 706, the difference between R(0) and the interval prior to theprevious interval, referred to as RR(−2), is calculated as a ratio toRR(0) and compared to a value of 0.1. At step 708, the sum of the twoprevious intervals RR(−1) and RR(−2) is compared to RR(0), and at step710, the difference of the two previous intervals RR(−1) and RR(−2) iscompared to RR(0). If any of these comparisons at steps 704 through 710are satisfied, the oversense counter is increased by one at step 712.

The comparisons made at steps 704 through 710 may also be represented bythe following equation:

MIN{|(RR _(i−1) −RR _(i))/RR _(i) |, |RR _(i−2) −RR _(i))/RR _(i)|,|((RR _(i−1) +RR _(i−2))−RR _(i))/RR _(i)|, |(|RR _(i−1) −RR _(i−2) −RR_(i))/RR _(i) |}<A   (1)

wherein RR_(i) is a given R-R interval starting with the first R-Rinterval sensed at arrhythmia detection, is the R-R_(i−1) intervalpreceding RR_(i), RR_(i−2) is the R-R interval preceding and RR_(i−1),is the predetermined value representing an expected variation in cardiaccycles, such as 0.1. If the minimum absolute value of the fourcomparisons shown in equation (1) is less than A, then two of theintervals RR_(i), RR_(i−1), or RR_(i−2) may be associated with a cardiacoversensed event.

If none of these comparisons are satisfied at steps 704 through 710,then the interval counter I is decreased by one at step 714, and itsabsolute value is compared to the number of intervals to evaluate atstep 716. If the number of intervals to evaluate has not been reached,the method 700 returns to step 704 and repeats the four comparisons atsteps 704 through 710 for the next previous interval prior to VFdetection. This process (steps 704 through 716) continues to step backthrough the sensed R-R intervals, starting from the R-R interval atdetection, until the desired number of intervals prior to VF detectionhas been analyzed.

After the desired number of intervals has been reached at step 716, thevalue of the oversense interval counter is compared to the number ofintervals evaluated at decision step 718. Criteria for recognizing acardiac oversensing pattern may be predefined, for example requiringthat a given percentage of the intervals prior to the detection event,for example 50%, satisfy the comparison of Equation (1) above or steps704 through 710.

In TABLE I, a sample sequence of sensed interval lengths is listed inthe first column with the corresponding minimum value determined fromEquation (1) listed in the second column. The value of the oversensedinterval count as Equation (1) is applied to each interval is shown inthe third column of TABLE I. For this example, 11 of 12 intervalssatisfy the Equation (1) indicating a pattern of cardiac oversensing.

TABLE I INTERVAL MINIMUM FROM OVERSENSE LENGTH EQUATION (1) COUNTERVALUE 250 0.08 1 270 0.0 2 270 0.0 3 280 0.04 4 270 0.0 5 270 0.0 6 2800.04 7 270 0.0 8 520 0.04 9 270 0.0 10 270 1.0 10 540 0.02 11 530 — —540 — —

If the cardiac oversensing criteria is not met at decision step 718,then the method 400 proceeds to step 463 (FIG. 7) to continue to searchfor other causes of oversensing that may lead to an inappropriatearrhythmia detection. If the cardiac oversensing criteria is met atdecision step 718, then a cardiac oversensing pattern is present asconcluded at step 720. Additional analysis of the stored EGM ispreferably performed by method 400 (FIG. 7) in order to identify thespecific type of oversensing, e.g. T-wave oversensing. Additionalverification is needed because the oversensing criteria described abovein conjunction with FIG. 9 could also be satisfied if regular intervals,for example associated with ventricular tachycardia, or sinustachycardia, are occurring.

Therefore, to verify that the arrhythmia detection is due to T-waveoversensing and not an appropriate VF detection, the method 400 of FIG.7 next compares consecutively sensed signal morphologies at decisionstep 445. If alternating morphologies are occurring, T-wave oversensingis diagnosed as the cause of the VF detection at step 450, and theepisode is identified as an inappropriate detection. ICD 10 determines arecommended corrective action to reduce the likelihood of oversensing atstep 521 (FIG. 8). Possible corrective actions for T-wave oversensinginclude, for example, increasing a sensitivity value of a sensingelectrode to decrease the sensitivity, reconfiguring the electrodeconfiguration from tip-to-ring (true bipolar) to tip-to-coil (integratedbipolar), increasing a decay constant of the sensing electrode, orincreasing the maximum auto-adjusting sensitivity threshold. Forinstance, ICD 10 may determine the appropriate corrective action to beincreasing the decay constant of the sensing electrode from 450milliseconds to 500 milliseconds. In addition, ICD 10 may automaticallyperform the recommended corrective actions dynamically in accordancewith the invention.

One method for performing the morphology analysis at step 445 isillustrated by the flow chart shown in FIG. 10. At step 601, designatedareas of memory are initialized for storing morphology templates. Atstep 602, a counter for counting a desired number of sensed events thatwill be analyzed is initialized to a value of 1. The morphology of thesensed event occurring at VF detection, referred to as R(I), is storedas a first template, TEMPLATE(1), at step 604. The morphology of thesensed event prior to R(I), referred to as R(I−1), is compared to thestored template, TEMPLATE(1), at step 606. If the morphology of R(I−1)approximately equals the TEMPLATE(1), as determined at decision step608, then R(I−1) is labeled as a TEMPLATE(1) match at step 618. Atemplate match indicates that R(I−1) is the same type of event as R(I).If the morphology of R(I−1) is different than TEMPLATE(1), it is storedas a second template, TEMPLATE(2), at step 620. A template match may bedetermined by calculating a correlation coefficient based on apoint-by-point comparison of a sampled signal and a stored template.Calculation of a correlation coefficient may be performed as generallydescribed in U.S. Pat. No. 5,193,550 issued to Duffin, incorporatedherein by reference in its entirety.

At step 622, the counter N is increased by 1, and at step 624 theabsolute value of the counter N is compared to the desired number ofsensed events to be evaluated. If the desired number has been reached,preferably on the order of 24 events, then the morphology analysis isterminated at step 626. Otherwise, the morphology analysis continues byreturning to step 606 to compare the next previous template, R(I−N) toTEMPLATE(1) at step 608. If the morphology of R(I−N) does not matchTEMPLATE(1), the method 600 determines if any other morphology templateshave been stored at decision step 610. If not, a new template is storedat step 620 with a template label.

Each time an event is found to be of a new morphology, in that it doesnot match a stored template, it is stored as a new template in one ofthe unoccupied, designated areas of memory. As new templates are stored,they may be labeled by consecutive numbers such that sensed eventsmatching a given template may be labeled accordingly. If other storedtemplates do exist, as determined at decision step 610, the morphologyof R(I−N) is compared to the other stored templates at step 612. IfR(I−N) matches any of the stored templates, as determined at decisionstep 614, the sensed event R(I−N) is labeled according to the matchingtemplate at step 616.

After completing the morphology analysis 600, the method 400 of FIG. 7can determine at decision step 445 if alternating signal morphologiesare occurring that would be evidence of T-wave oversensing. For example,criteria for detecting alternating signal morphologies may require thatalternating morphologies occur during at least one sequence of sixconsecutive events or during two sequences of five consecutive events.If so, the cardiac oversensing pattern detected at step 440 and thealternating signal morphologies detected at step 445 indicate that thedetected arrhythmia is inappropriate due to T-wave oversensing asconcluded at step 450. As described above, one such recommended orautomatic corrective action could be to reprogram the ventricularsensitivity.

If the signal morphologies are not alternating at step 445, the method400 determines if short intervals are consecutive with long intervals atstep 455. As illustrated in FIG. 1, alternating short and long intervalsevidences R-wave oversensing (also referred to as R-wave doublecounting), as diagnosed at step 460. At decision step 455, apredetermined criteria for detecting the presence of short and longintervals indicative of R-wave oversensing may be used. R-waveoversensing will typically result in an interval of less than 160milliseconds followed by an interval greater than 200 milliseconds in arepetitive manner. Therefore, criteria for recognizing a short-longinterval pattern as evidence of R-wave oversensing may require, forexample, at least four interval pairs comprising consecutive short andlong intervals occurring within the 16 intervals prior to the arrhythmiadetection, wherein the short interval is less than 160 milliseconds andthe long interval is greater than 200 milliseconds. ICD 10 determines arecommended corrective action to reduce the likelihood of oversensing atstep 521 (FIG. 8). Possible corrective actions for R-wave oversensinginclude, for example, increasing a sensitivity value of a sensingelectrode to decrease the sensitivity, reconfiguring the sensingelectrode configuration from tip-to-ring (true bipolar) to tip-to-coil(integrated bipolar), or increasing a blanking period of the sensingelectrode. For instance, ICD 10 may determine the appropriate correctiveaction to be increasing the blanking period of the sensing electrodefrom 120 milliseconds to 140 milliseconds. In addition, ICD 10 mayautomatically perform the recommended corrective actions dynamically inaccordance with the invention.

If the presence of short and long intervals is not detected at step 455,cardiac oversensing is not verified, and the method 400 proceeds to step465 (FIG. 8) to evaluate the EGM signals for the presence of noise. Ifthe cardiac oversensing criteria was not met initially at decision step440, the method 400 proceeds to step 463 to verify that an irregularpattern of consecutive short and long intervals does not exist.

Cardiac oversensing may still be occurring but in an irregular patternif the heart rhythm is an irregular tachycardia. Therefore, consecutiveshort and long intervals of varying lengths can exist if cardiacoversensing is occurring during irregular ventricular tachycardia. Theirregular ventricular tachycardia may be detected as VF due to cardiacoversensing, such as R-wave oversensing, but in this case an arrhythmiadoes exist making the arrhythmia detection appropriate. If consecutiveshort and long intervals are recognized at decision step 463, thearrhythmia detection is identified as an appropriate detection at step437, otherwise the method 400 proceeds to step 465 to evaluate the EGMfor the presence of noise.

If one or more near-field EGM signals has been stored, they are examinedat step 465 for saturation or bursts of noise. Saturation or bursts ofnoise on the near-field EGM are evidence of a lead fracture or poor leadconnection, as previously shown in FIG. 2C. Saturation may be detectedas a predetermined minimum number of consecutive digitized samples equalto the maximum analog-to-digital conversion unit. The analog EGM signalis converted to a digitized signal by sampling the analog signal at agiven sampling frequency, for example every 8 milliseconds. The analogvoltage amplitude of each sampled point is converted to a digital unit,referred to as an “A/D unit,” using an analog-to-digital conversionfactor. One ND unit may equal 8 mV, for example, with a maximum ND unitamplitude of 127 units. Therefore, in one embodiment, saturation of thenear-field EGM may be detected when at least five consecutively sampledpoints equal the maximum ND unit amplitude of 127 units.

If a lead fracture has occurred or the lead is poorly connected,intermittent bursts of noise will interrupt periods of low frequency onthe near-field EGM signal. A method 650 for recognizing noise burststhat may be performed at decision step 465 is shown by the flow chart ofFIG. 11. In order to recognize noise bursts, low frequency signalsegments and noise segments must be discriminated in the EGM signal. Atstep 652, the low frequency EGM segments are identified. A low frequencysignal sample may be defined as one in which the change in amplitudecompared to the previous sample is less than a given maximum number ofND units, for example less than 5 A/D units. Consecutive low frequencysignal samples form a low frequency signal segment. For example, asequence of digitized sample point amplitudes is listed in TABLE IIbelow.

TABLE II 100 25 0 4 3 2 0 0 5 10 50 −30 −40

A change in amplitude of less than 5 A/D units is recognized between thethird and fourth samples, 0 and 4. These samples are at the start of alow frequency segment totaling six samples including the samples havingamplitudes of: 0, 4, 3, 2, 0, and 0. All other samples in the abovesequence have a change in ND amplitude of 5 units or more.

At step 654, noise segments of the EGM are identified. A unit of noisemay be defined as two consecutive signal samples that vary in amplitudeby more than a predetermined number of A/D units, for example 3 A/Dunits, and represent a change in amplitude direction. For example, inthe sequence of TABLE II, the only noise unit exists between the points50 and −30. The amplitude change between 50 and −30 represents a changein direction, from positive going from the previous sample 10 to 50, tonegative going from 50 to −30, and a change in amplitude of greater than3 A/D units.

A noise burst comprises a group of low frequency signal segments withshort, intervening noise segments. Therefore, at step 656, low frequencygroups are identified and counted. A low frequency group may beidentified as two or more low frequency segments that are at least 20sample points in length with a difference in length of 10 sample pointsor less. For example, the number of sampled points in each of a numberof detected low frequency segments is listed in TABLE III below.

TABLE III 6 10 12 14 20 21 23 23 26 30 32 34

The sample sequence in TABLE III includes a group of six low frequencysegments having 20, 21, 23, 23, 26, and 30 sample points each. Thesegments having less than 20 sample points are not considered part of agroup according to the above defined criteria. The segments of 32 and 34sample points each are more than 10 sample points greater than thesegments of 20 and 21 sample points and are therefore not included inthe group. Another group of low frequency segments includes the fivesegments of 23, 23, 26, 30, and 32 sample points. Each of these segmentsare greater than 20 sample points in length and their lengths are within10 sample points of each other. In this example, the largest group ofthe low frequency segments is a group of six low frequency segments.

After identifying the low frequency segments and the noise segments,numerous criteria may be set forth for identifying a noise burst basedon the number of low frequency groups, the length of low frequencysegments, the length of noise segments, and/or the overall percentage ofnoise present in the EGM signal. The percentage of noise in the EGMsignal may be determined as the total number of noise units divided bythe total number of EGM samples multiplied by 100 percent. A set ofcriteria for identifying noise bursts used by method 650 of FIG. 11 hasa first criterion limiting the largest group of low frequency segmentsto less than five segments, as determined at decision step 658. If thelargest low frequency group has five or more segments, a conclusion ismade at step 660 that noise bursts are not present on the EGM signal. Ifthe largest low frequency group is less than five segments and themaximum noise segment during the entire EGM segment analyzed is four ormore noise units in length as determined at decision step 662, and lessthan 20% of the total EGM signal is identified as noise at decision step664, then a noise burst is present as concluded at step 666.

Alternatively, if the largest low frequency group is less than 5segments (decision step 658), the maximum noise segment is at least twonoise units as determined at decision step 668, and the maximum lowfrequency segment in the entire EGM segment analyzed is greater than 30sample points as determined at decision step 670 with less than 20% ofthe EGM signal identified as noise at decision step 664, then a noiseburst is present as concluded at step 666. If these criteria are not metat steps 658, 662, 664, 668 and 670, then the conclusion is made thatnoise bursts are not present at step 672.

If either saturation or a noise burst is found in a near-field EGM atdecision step 465 (FIG. 7), then a lead fracture or poor lead connectionis likely. If the lead carrying the sensing electrodes has beenimplanted for less than two months, as determined at step 470, the noiseis likely due to poor connection of the lead to the implanted device.The time that an ICD has been implanted may be known, for example, by atime-stamp that is made when VF detection is first programmed to “on.”This information is made available when stored EGM data is saved to adiskette in commercially available devices, for example in the Model7275 GEM® III Dual Chamber Implantable Cardioverter Defibrillatoravailable from Medtronic, Inc., Minneapolis, Minn. If the implant timeis known to be less than two months, a diagnosis of oversensing due topoor lead connection is made at step 475, and the episode is identifiedas an inappropriate arrhythmia detection. A recommended correctiveaction could be to tighten the set screws on the connector block of theICD 10.

If the lead has been implanted for more than two months, theintermittent noise bursts and/or signal saturation are likely due to alead fracture, resulting in an inappropriate arrhythmia detection. Thisdiagnosis is made at step 480. Further investigation through x-ray orinvasive procedures may need to be performed to verify a lead fractureand, if found, repair or replace the lead.

If a near-field EGM has not been stored or if no saturation or noisebursts are present on a near-field EGM, as determined at decision step465, the method 400 proceeds to step 485 to evaluate both the near-fieldand far-field EGM signals for noise, with priority given to thenear-field EGM signal if it has been stored. At decision step 485, themethod 400 looks for an interval pattern evidencing noise. Typically,very short R-R intervals will be sensed in the presence of noise.Therefore one criteria for detecting a noise interval pattern atdecision step 485 it to detect at least two R-R intervals of less than160 milliseconds out of the last 18 sensed R-R intervals. If a noisepattern is not present, the method 400 concludes at step 490 byclassifying the arrhythmia detection as appropriate.

If a noise pattern is present, the method 400 proceeds to evaluate thenear-field and/or far-field EGM to determine the type of noise present.Saturation or noise bursts associated with a lead fracture or poor leadconnection are not observed on a far-field EGM signal. Therefore, themethod 400 first analyzes the EGM to exclude other forms of noise thatmay cause an inappropriate arrhythmia detection, such as electromagneticinterference or other myopotentials.

At step 500, the near-field and/or far-field EGM signal is analyzed todetermine what percentage of the signal is noise. An extremely noisy EGMepisode, as can occur with electromagnetic interference, may be definedas an episode containing greater than a predefined percentage of noiseunits, for example greater than 60% of the EGM signal samples areidentified as noise units. If the EGM signal is found to be extremelynoisy at decision step 500, the detected arrhythmia is identified asinappropriate due to electromagnetic interference (EMI) at step 505.Electromagnetic interference is typically present as high-frequency,continuous noise, producing an extremely noisy (greater than 60% noise)EGM signal as previously illustrated in FIG. 2A.

If the EGM signal is not found to be extremely noisy at decision step500, the sensed R-R interval distribution is examined at step 510 todetermine if the intervals represent a typical VF interval distribution.An average R-R cycle length sensed during VF is typically around 220milliseconds. If sensed R-R cycle lengths are much shorter or muchlonger than a typical VF cycle length, noise is likely to be present. Atdecision step 510, the method 400 may determine if any R-R cycle lengthsare less than a predetermined minimum VF cycle length or greater than apredetermined maximum VF cycle length. These minimum and maximum cyclelengths represent the range of an expected VF cycle length distribution.A criterion for detecting a non-VF cycle length distribution at decisionstep 510, therefore, may require a given percentage, for example 50%, ofthe R-R intervals to be outside the typical VF distribution. In oneembodiment, at least 6 of the last 12 R-R intervals must be less than200 milliseconds or greater than 300 milliseconds with at least one ofthese intervals being greater than 300 milliseconds in order to detect anon-VF cycle length distribution. If a typical VF interval distributionis found at decision step 510, then the arrhythmia detection isidentified as an appropriate detection at step 490. If a non-VFdistribution is found, the method 400 continues to evaluate the EGMsignal for noise associated with non-cardiac myopotentials.

Oversensing of myopotential noise is typically intermittent and of lowerfrequency than EMI oversensing, as previously shown in FIGS. 2A and 2B.Myopotential noise may produce a very noisy EGM signal comprising, forexample, greater than 20% noise units but less than 60% noise units. Ifthe EGM signal is determined to be very noisy at decision step 515, aninappropriate arrhythmia detection due to myopotential noise isdiagnosed at step 520. ICD 10 may determine a recommended correctiveaction to reduce the likelihood of oversensing at step 521. Possiblecorrective actions for oversensing caused by a non-cardiac origin, e.g.,myopotentials or EMI, include increasing a sensitivity value of asensing electrode to decrease the sensitivity, reconfiguring theelectrode configuration from tip-to-ring (true bipolar) to tip-to-coil(integrated bipolar), increasing a decay constant of the electrode, orincreasing the maximum auto-adjusting sensitivity threshold. Forinstance, ICD 10 may determine the appropriate corrective action to beincreasing the sensitivity value of the electrode from 0.3 millivolts to0.45 millivolts. In addition, ICD 10 may automatically perform therecommended corrective actions dynamically in accordance with theinvention.

If the EGM is not found to be very noisy at step 515, the baseline ofthe far-field EGM is examined. If VF is actually occurring, the EGMsignal will be at the baseline value for only very short samplesegments. If an inappropriate detection has been made due to a leadfracture or poor lead connection, longer EGM baseline segments will bepresent during sinus rhythm. In addition, a higher amplitude eventconsistent with a normal R-wave will normally exist in contrast to thelower amplitude fibrillation waves. Therefore, at decision step 525, themethod 400 examines the far-field EGM for relatively long periods ofbaseline with at least one relatively large amplitude event, both ofwhich would not be present during real VF but would represent a possiblelead fracture or poor connection.

A segment of baseline may be identified as a segment in which the sum ofthe absolute value of the amplitudes of consecutive sampled points isless than a predetermined number of A/D units, for example 5 A/D units.If, at step 525, at least one baseline segment exceeding 160milliseconds in length is present in the far-field EGM with at least onesample point greater than 2.5 mV, the arrhythmia detection is identifiedas inappropriate. If the lead carrying the sensing electrodes has beenimplanted for less than two months (decision step 470), theinappropriate detection is diagnosed as oversensing of noise due to alead fracture at step 480. If the lead has been implanted less than twomonths, a diagnosis of oversensing due to poor lead connection is madeat step 475. If a relatively long baseline and higher amplitude samplecannot be identified at decision step 525, the arrhythmia detection isan appropriate detection (step 490).

Thus, the methods shown in FIGS. 5 through 11 provide automaticidentification of oversensing. Moreover, the methods described aboveallow causes of oversensing, which may lead to inappropriate arrhythmiadetection, to be specifically identified based on an analysis of sensedEGM interval patterns and signal morphologies. Numerous sources ofoversensing, which can be both cardiac and non-cardiac in origin, aresystematically identified or eliminated by the methods included in thepresent invention, providing a physician with a powerful andtime-savings tool for trouble-shooting the problem of oversensing. Moreaccurate sensing of the heart rhythm may be achieved by identifying andautomatically correcting oversensing, thereby allowing appropriatestimulation therapies to be delivered only when needed.

FIG. 12 is an exemplary cardiac electrogram illustrating T-waveoversensing as well as exemplary automatic corrective actions to reducethe likelihood of T-wave oversensing. Specifically, the exampleillustrated in FIG. 12 shows an exponential decay curve 800 thatillustrates the sensitivity of a sensing electrode, such as aventricular electrode, after application of a pacing pulse. In otherwords, the sensitivity of the sensing electrode changes as a function ofdecay curve 800. ICD 10 operates in accordance with the sensitivity,e.g., sensitivity as a function of exponential decay curve 800, of thesensing electrode for a plurality of cardiac cycles. T-wave oversensingoccurs at the first T-wave because a sensitivity of the sensingelectrode is below the potential of the T-wave. In accordance with theinvention, however, ICD 10 automatically performs one or more correctiveactions to reduce the likelihood of oversensing. As described above, thecorrective actions are performed in a dynamic fashion.

One such corrective action is to increase a maximum auto-adjustingsensitivity threshold of the sensing electrode such that the sensitivityof the sensing electrode is above the potential of the T-wave, asillustrated by decay curve 802 at the second T-wave. For example, themaximum auto-adjusting sensitivity threshold may be increased from 75%of the R-wave potential to 95% of the R-wave potential. In other words,the exponential decay curve representing the sensitivity of the sensingelectrode is shifted up such that it is above the T-wave potential.

Another automatic corrective action that may be performed by ICD 10includes increasing a decay constant of the sensing electrode, asillustrated decay curve 804 at the third T-wave. For example, the decayconstant may be increased from 450 milliseconds to 500 milliseconds inorder to decrease the exponential decay of the sensing electrode, thusdecreasing the sensitivity such that the T-wave potential is notdetected. Although illustrated separately, IMD 10 may use bothcorrective actions simultaneously to reduce the likelihood ofoversensing.

The illustrated automatic corrective actions are by no means the onlyautomatic corrective actions that may be taken to reduce the likelihoodof T-wave oversensing. Other automatic corrective actions includechanging an electrode configuration of the sensing electrode form atip-to-ring configuration (e.g., true bipolar configuration) to atip-to-coil configuration (e.g., integrated bipolar configuration).Further, the sensitivity of the sensing electrode may be decreased,e.g., by increasing the sensitivity value of the sensing electrode.Although described in terms of T-wave oversensing, these automaticcorrective actions may be applied to reduce the likelihood of othercardiac or non-cardiac oversensing, such as myopotential oversensing.

FIG. 13 is an exemplary cardiac electrogram illustrating R-waveoversensing (i.e., R-wave double counting) as well as exemplaryautomatic corrective actions to reduce the likelihood of R-waveoversensing. Specifically, the example illustrated in FIG. 13 shows ablanking period 806 representative of a period of time when a sensingelectrode, such as a ventricular electrode, is shut off afterapplication of a pacing pulse. R-wave oversensing occurs at the firstR-wave because the blanking period of the sensing electrode ends beforethe R-wave potential is below a sensitivity of the sensing electrode.R-wave oversensing can occur, for example, when an R-wave complex iswidened due to conditions such as bundle branch block or wide complexventricular tachycardia. In accordance with the invention, however, ICD10 automatically performs one or more corrective actions to reduce thelikelihood of oversensing.

One such corrective action may be to increase the blanking period suchthat it covers the entire R-wave complex, as illustrated by blankingperiod 808. For example, the blanking period may be increased from 120milliseconds to 140 milliseconds for a patient who experiences a widenedR-wave complex due to bundle branch block.

The illustrated automatic corrective action is by no means the onlyautomatic corrective actions that may be taken to reduce the likelihoodof R-wave oversensing or R-wave double counting. Other automaticcorrective actions include changing an electrode configuration of thesensing electrode form a tip-to-ring configuration (e.g., true bipolarconfiguration) to a tip-to-coil configuration (e.g., integrated bipolarconfiguration). Further, the sensitivity of the sensing electrode may bedecreased, e.g., by increasing the sensitivity value of the sensingelectrode. Although described in terms of R-wave oversensing, theseautomatic corrective actions may be applied to reduce the likelihood ofother cardiac or non-cardiac oversensing.

The detailed descriptions of the preferred embodiments provided hereinyield a sensitive and specific method for analyzing EGM signals andsensed interval patterns to diagnose oversensing of cardiac ornon-cardiac signals and automatically adjusting sensing parameters,electrode configurations, and the like to reduce the likelihood ofreoccurrence of the oversensing. Numerous variations of the describedembodiments are possible for practicing the invention. Therefore, theembodiments described herein should be considered exemplary, rather thanlimiting, with regard to the following claims. These and otherembodiments are within the scope of the following claims.

1. A method of operating an implantable medical device comprising:detecting an arrhythmia of a heart of a patient; identifying thedetected arrhythmia as an inappropriate detection due to oversensing;and cancelling a therapy upon identifying the detected arrhythmia as aninappropriate detection due to oversensing.
 2. The method of claim 1,further comprising automatically performing a corrective action toprevent future inappropriate arrhythmia detections in response toidentifying the detected arrhythmia as an inappropriate detection due tooversensing.
 3. The method of claim 2, further comprising identifying anorigin of oversensing, wherein automatically performing the correctiveaction comprises automatically performing the corrective action based onthe identified origin.
 4. The method of claim 3, wherein identifying theorigin of the oversensing comprises identifying the origin as one ofcardiac origin and non-cardiac origin.
 5. The method of claim 3, whereinidentifying the origin of the oversensing comprises one of identifyingthe origin of oversensing as one of far-field R-wave oversensing, T-waveoversensing, R-wave oversensing, poor lead connection, lead fracture,electromagnetic interference (EMI) and myopotential noise.
 6. The methodof claim 2, wherein automatically performing the corrective actioncomprises automatically adjusting at least one sensing parameter of theimplanted medical device in response to identifying the detectedarrhythmia as an inappropriate detection due to oversensing.
 7. Themethod of claim 6, wherein automatically adjusting the at least onesensing parameter includes automatically adjusting at least one of aprogrammed sensitivity of a sensing electrode, a programmed threshold ofa sensing electrode, a programmed decay constant of a sensing electrode,a programmed decay delay of a sensing electrode, a programmed blankingperiod of a sensing electrode, and an electrode configuration of asensing electrode.
 8. The method of claim 2, wherein the automaticcorrective action is performed iteratively and incrementally, and aftereach adjustment determining whether oversensing persists.
 9. The methodof claim 1, wherein identifying the detected arrhythmia as aninappropriate detection due to oversensing comprises: determiningwhether a sum of consecutive interval differences is less than apredetermined maximum; determining whether an interval pattern isindicative of cardiac oversensing; determining whether signalmorphologies of consecutively sensed events alternate; and identifyingthe detected arrhythmia as an inappropriate detection due to oversensingwhen the sum of consecutive interval differences is not less than thepredetermined maximum, the interval pattern is indicative of cardiacoversensing, and alternating signal morphologies occur.
 10. The methodof claim 9, further comprising: analyzing consecutive intervals todetermine whether there are alternating short and long intervals; andidentifying the detected arrhythmia as an inappropriate detection due tooversensing when the sum of consecutive interval differences is not lessthan the predetermined maximum, the interval pattern is indicative ofcardiac oversensing, alternating signal morphologies do not occur, andconsecutive intervals have alternating short and long intervals.
 11. Themethod of claim 1, wherein identifying the detected arrhythmia as aninappropriate detection due to oversensing comprises identifying thedetected arrhythmia as an inappropriate detection due to oversensingusing intracardiac electrograms.
 12. An implantable medical devicecomprising: sensing circuitry that obtains signals sensed by one or moreelectrodes; and a processor that analyzes the sensed signals to detectan arrhythmia of a heart of a patient; identify the detected arrhythmiaas an inappropriate detection due to oversensing, and cancel a therapyupon identifying the detected arrhythmia as an inappropriate detectiondue to oversensing.
 13. The device of claim 12, wherein the processorautomatically performs a corrective action to prevent futureinappropriate arrhythmia detections in response to identifying thedetected arrhythmia as an inappropriate detection due to oversensing.14. The device of claim 13, wherein the processor identifies an originof oversensing, wherein automatically performing the corrective actioncomprises automatically performing the corrective action based on theidentified origin.
 15. The device of claim 14, wherein the origin of theoversensing is identified as one of cardiac origin and non-cardiacorigin.
 16. The device of claim 14, wherein the origin of theoversensing is identified as one of far-field R-wave oversensing, T-waveoversensing, R-wave oversensing, poor lead connection, lead fracture,electromagnetic interference (EMI) and myopotential noise.
 17. Thedevice of claim 13, wherein the processor automatically adjusts at leastone sensing parameter of the implanted medical device in response toidentifying the detected arrhythmia as an inappropriate detection due tooversensing.
 18. The device of claim 17, wherein the processorautomatically adjusts at least one of a programmed sensitivity of thesensing circuitry, a programmed blanking period of the sensingcircuitry, a programmed threshold of the sensing circuitry, a programmeddecay constant of the sensing circuitry, a programmed decay delay of thesensing circuitry, and an electrode configuration.
 19. The device ofclaim 13, wherein the processor performs the corrective actioniteratively and incrementally, and after each adjustment determineswhether oversensing persists.
 20. The device of claim 12, wherein theprocessor: determines whether a sum of consecutive interval differencesis less than a predetermined maximum; determines whether an intervalpattern is indicative of cardiac oversensing; determines whether signalmorphologies of consecutively sensed events alternate; and identifiesthe detected arrhythmia as an inappropriate detection due to oversensingwhen the sum of consecutive interval differences is not less than thepredetermined maximum, the interval pattern is indicative of cardiacoversensing, and alternating signal morphologies occur.
 21. The deviceof claim 20, wherein the processor: analyzes consecutive intervals todetermine whether there are alternating short and long intervals; andidentifies the detected arrhythmia as an inappropriate detection due tooversensing when the sum of consecutive interval differences is not lessthan the predetermined maximum, the interval pattern is indicative ofcardiac oversensing, alternating signal morphologies do not occur, andconsecutive intervals have alternating short and long intervals.
 22. Animplantable medical device comprising: means for detecting an arrhythmiaof a heart of a patient; means for identifying the detected arrhythmiaas an inappropriate detection due to oversensing; and means forcancelling a therapy upon identifying the detected arrhythmia as aninappropriate detection due to oversensing.
 23. The device of claim 22,further comprising means for automatically performing a correctiveaction to prevent future inappropriate arrhythmia detections in responseto identifying the detected arrhythmia as an inappropriate detection dueto oversensing.
 24. The device of claim 23, wherein the identifyingmeans identify an origin of oversensing and the means for automaticallyperforming the corrective action perform the corrective action based onthe identified origin.
 25. A computer-readable medium comprisinginstructions that when executed by a processor cause the processor to:detect an arrhythmia of a heart of a patient; identify the detectedarrhythmia as an inappropriate detection due to oversensing; and cancela therapy upon identifying the detected arrhythmia as an inappropriatedetection due to oversensing.